Maternal Effects on Embryonic Development and Survival in Walleyes of Lake Nipissing, Ontario
Bibliographic record
Abstract
Abstract Life history theory predicts that females may increase reproductive allocation with advancing age as the probability for future reproduction diminishes. In iteroparous fishes, increasing age is usually accompanied by increasing fecundity, but evidence of increasing offspring quality is less consistent. We examined the developmental rate and survival of Walleye Sander vitreus embryos with respect to female age, size, condition, and various ova traits in an exploited stock dominated by young spawners. Embryo batches from individual females were collected in the field on multiple dates and reared to hatch under controlled conditions in both flow‐through and static incubation systems. Survival and thermal inputs to hatch (TU50) were analyzed with respect to spawn date, incubation method, and both maternal and ova traits. Spawning date had a relatively strong effect on embryo survival but only a minor effect on TU50, whereas incubation method had a small effect on survival but a stronger effect on TU50. Embryos reared in static incubators required greater thermal inputs to reach hatch. Using a model selection approach to assess the effects of maternal and ova traits, we found that neither maternal age nor size were strong predictors of survival or TU50. Instead, survival was more strongly related to egg size and fatty acid composition, and TU50 was not strongly related to any maternal or ova trait. Our results suggest that the nature and magnitude of maternal effects on early development and survival may vary among Walleye stocks, modified by physical conditions during incubation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".